benchmarkfcns.multifidelity.bentcigar

benchmarkfcns.multifidelity.bentcigar(arg0: Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]', 'flags.c_contiguous']) → Annotated[numpy.typing.NDArray[numpy.float64], '[m, n]']

Computes the value of the multi-fidelity Bent Cigar function. SCORES = bentcigar(X) computes the value of the Bent Cigar function at point X. multifidelity.bentcigar accepts a matrix of size M-by-N and returns a matrix SCORES of size M-by-2.

Mathematical Definition

\[f(\mathbf{x}) = x_1^2 + 10^6 \sum_{i=2}^n x_i^2\]

Visualization